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---
license: apache-2.0
tags:
- automatic-speech-recognition
- NbAiLab/NPSC
- generated_from_trainer
model-index:
- name: wav2vec2-xlsr-1B-NPSC-NN
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-xlsr-1B-NPSC-NN
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the NBAILAB/NPSC - 16K_MP3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4562
- Wer: 0.1531
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.6894 | 1.08 | 500 | 1.2423 | 0.8619 |
| 0.7543 | 2.15 | 1000 | 0.5956 | 0.3817 |
| 0.5481 | 3.23 | 1500 | 0.5043 | 0.3246 |
| 0.4661 | 4.3 | 2000 | 0.4813 | 0.2793 |
| 0.3901 | 5.38 | 2500 | 0.4371 | 0.2592 |
| 0.3512 | 6.45 | 3000 | 0.4216 | 0.2458 |
| 0.3016 | 7.53 | 3500 | 0.3814 | 0.2257 |
| 0.278 | 8.6 | 4000 | 0.4151 | 0.2145 |
| 0.2435 | 9.68 | 4500 | 0.4816 | 0.2130 |
| 0.2122 | 10.75 | 5000 | 0.4489 | 0.2137 |
| 0.1949 | 11.83 | 5500 | 0.3978 | 0.2063 |
| 0.1929 | 12.9 | 6000 | 0.3823 | 0.2026 |
| 0.1757 | 13.98 | 6500 | 0.3409 | 0.1965 |
| 0.1771 | 15.05 | 7000 | 0.3844 | 0.1936 |
| 0.1452 | 16.13 | 7500 | 0.3749 | 0.1900 |
| 0.1341 | 17.2 | 8000 | 0.4407 | 0.2026 |
| 0.13 | 18.28 | 8500 | 0.4253 | 0.1883 |
| 0.1183 | 19.35 | 9000 | 0.4311 | 0.1880 |
| 0.118 | 20.43 | 9500 | 0.4431 | 0.1882 |
| 0.1123 | 21.51 | 10000 | 0.4753 | 0.1820 |
| 0.1037 | 22.58 | 10500 | 0.4087 | 0.1834 |
| 0.1066 | 23.66 | 11000 | 0.4151 | 0.1845 |
| 0.0977 | 24.73 | 11500 | 0.4367 | 0.1783 |
| 0.0968 | 25.81 | 12000 | 0.4237 | 0.1756 |
| 0.0835 | 26.88 | 12500 | 0.4729 | 0.1781 |
| 0.0919 | 27.96 | 13000 | 0.4153 | 0.1701 |
| 0.0677 | 29.03 | 13500 | 0.4317 | 0.1693 |
| 0.0726 | 30.11 | 14000 | 0.4380 | 0.1736 |
| 0.066 | 31.18 | 14500 | 0.4384 | 0.1681 |
| 0.0713 | 32.26 | 15000 | 0.4215 | 0.1629 |
| 0.0605 | 33.33 | 15500 | 0.4574 | 0.1714 |
| 0.0632 | 34.41 | 16000 | 0.4343 | 0.1642 |
| 0.0567 | 35.48 | 16500 | 0.4231 | 0.1601 |
| 0.0556 | 36.56 | 17000 | 0.4404 | 0.1667 |
| 0.0426 | 37.63 | 17500 | 0.4459 | 0.1625 |
| 0.0445 | 38.71 | 18000 | 0.4484 | 0.1629 |
| 0.0463 | 39.78 | 18500 | 0.4508 | 0.1596 |
| 0.0448 | 40.86 | 19000 | 0.4395 | 0.1605 |
| 0.0434 | 41.94 | 19500 | 0.4490 | 0.1607 |
| 0.0347 | 43.01 | 20000 | 0.4772 | 0.1582 |
| 0.0332 | 44.09 | 20500 | 0.4729 | 0.1582 |
| 0.037 | 45.16 | 21000 | 0.4559 | 0.1573 |
| 0.0328 | 46.24 | 21500 | 0.4664 | 0.1560 |
| 0.0366 | 47.31 | 22000 | 0.4543 | 0.1543 |
| 0.0377 | 48.39 | 22500 | 0.4507 | 0.1560 |
| 0.0331 | 49.46 | 23000 | 0.4567 | 0.1533 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
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